Statistical Evaluation of Metaproteomics and 16S rRNA Amplicon Sequencing Techniques for Study of Gut Microbiota Establishment in Infants with Cystic Fibrosis

Newborn screening for cystic fibrosis (CF) can identify affected but asymptomatic infants. The selection of omic technique for gut microbiota study is crucial due to both the small amount of feces available and the low microorganism load. Our aims were to compare the agreement between 16S rRNA amplicon sequencing and metaproteomics by a robust statistical analysis, including both presence and abundance of taxa, to describe the sequential establishment of the gut microbiota during the first year of life in a small size sample (8 infants and 28 fecal samples). The taxonomic assignations by the two techniques were similar, whereas certain discrepancies were observed in the abundance detection, mostly the lower predicted relative abundance of Bifidobacterium and the higher predicted relative abundance of certain Firmicutes and Proteobacteria by amplicon sequencing. During the first months of life, the CF gut microbiota is characterized by a significant enrichment of Ruminococcus gnavus, the expression of certain virulent bacterial traits, and the detection of human inflammation-related proteins. Metaproteomics provides information on composition and functionality, as well as data on host-microbiome interactions. Its strength is the identification and quantification of Actinobacteria and certain classes of Firmicutes, but alpha diversity indices are not comparable to those of amplicon sequencing. Both techniques detected an aberrant microbiota in our small cohort of infants with CF during their first year of life, dominated by the enrichment of R. gnavus within a human inflammatory environment. IMPORTANCE In recent years, some techniques have been incorporated for the study of microbial ecosystems, being 16S rRNA gene sequencing being the most widely used. Metaproteomics provides the advantage of identifying the interaction between microorganisms and human cells, but the available databases are less extensive as well as imprecise. Few studies compare the statistical differences between the two techniques to define the composition of an ecosystem. Our work shows that the two methods are comparable in terms of microorganism identification but provide different results in alpha diversity analysis. On the other hand, we have studied newborns with cystic fibrosis, for whom we have described the establishment of an intestinal ecosystem marked by the inflammatory response of the host and the enrichment of Ruminococcus gnavus.

Validity of the MarkWiiR for kinematic analysis during walking and running gaits

The aim of this study was to validate the MarkWiiR (MW) captured by the Nintendo Wii-Remote (100-Hz) to assess active marker displacement by comparison with 2D video analysis. Ten participants were tested on a treadmill at different walking (1<6 km · h⁻¹) and running (10<13 km · h⁻¹) speeds. During the test, the active marker for MW and a passive marker for video analysis were recorded simultaneously with the two devices. The displacement of the marker on the two axes (x-y) was computed using two different programs, Kinovea 0.8.15 and CoreMeter, for the camera and MW, respectively. Pearson correlation was acceptable (x-axis r≥0.734 and y-axis r≥0.684), and Bland–Altman plots of the walking speeds showed an average error of 0.24±0.52% and 1.5±0.91% for the x- and y-axis, respectively. The difference of running speeds showed average errors of 0.67±0.33% and 1.26±0.33% for the x- and y-axes, respectively. These results demonstrate that the two measures are similar from both the x- and the y-axis perspective. In conclusion, these findings suggest that the MarkWiiR is a valid and reliable tool to assess the kinematics of an active marker during walking and running gaits.